totaling 26 square kilometers in the Kenauk Nature preserve, one of the largest private nature reserves in North America. Located in the southwest of Quebec, the property encompasses 26,000 ha (65,000 ac) of heterogenous forest. For the data analysis and classification they acquired two 30-cm WorldView-3 satellite images, orthorectified them with a 5-m Lidar DEM and then mosaicked them. The Lidar data was also used to create a canopy height model (CHM) which they overlaid on the mosaic. Based on existing aerial imagery, researchers first identified relevant trees for field data collection. Using Trimble Pro 6H GPS receivers, teams navigated to the pre-selected trees in each AOI to capture their position, height, diameter, and species type. In total, they surveyed 515 trees, which they further processed into 338 reference samples for both training eCognition and validating the results. With the data sources prepared, Varin and his team were ready to test the eCognition classification workflow. Using advanced artificial intel - ligence and machine-learning algorithms, the software focused only on trees higher than 17 meters and used the WorldView mosaic and the CHM to first segment the whole AOI into individual tree crowns. From there it considered pre-defined object thresholds and textural indices to identify and delineate Broadleaf trees from Conifers, and then it targeted the individual species within those two groups. In about two hours, eCognition classified 11 tree types including Red Oak, Sugar Maple, Balsam Fir, Eastern Hemlock, and White Spruce. “The delineation process was surprisingly quick and precise,” says Varin. “The overall accuracy for Conifers was 94 percent. That is very good considering the complex heterogeneity of the AOI.” The CERFO team shared the results with forest managers, many of whom can already see the potential value in having a tree-specific data layer in their GIS for developing targeted harvesting or planning. They also recognize the value of this OBIA-based approach as a viable enhancement to the traditional classifying and mapping methods using photogrammetry. Supported by that positive feedback, Varin and colleagues are furthering their eCognition work to refine the approach and provide forest manag - ers with new seeds of information for their management operations. “A significant research and development advantage with eCognition is that it’s incredibly teachable,” says Varin. “Through this project we developed a workflow with which we can repeat the same process or we can challenge the software to extract a whole new set of details that we haven’t produced before. Because it absorbs various forms of data, strictly follows rules and adapts when the information or rules change, it really is an ideal student.” Such a learning environment could lead to exciting new branches of tree analysis for the serious business of forest management.
His recent research has centered on using very high-resolution satellite imagery, Lidar data, and Trimble’s eCognition OBIA software to study the ability to automatically identify individual Broadleaf and Conifer trees in dense, complex forests––trees that are especially challenging to classify. “Identifying and delineating Broadleaf trees are difficult because their branches are interlaced and the individual tree crowns are not always pure,” says Varin. “It is particularly difficult to classify them in stands that contain trees of the same height and age. And in Broadleaf-domi- nant forests, Conifer trees like Balsam Fir are challenging because they are generally small and they’ll be in the Broadleaf’s shadow. However, the analytical intelligence of OBIA software makes classifying and mapping these tree types possible.” Based on the promising results, Varin may be cultivating a new path for efficient, targeted tree management. Tree-specific Varin and colleagues not only wanted to test the automated classi- fication method on Broadleaf and Conifer species, they wanted to test it in a complex forest. They chose three areas of interest (AOI) Presque-åle: Antoine Desrochers collects data on an American Basswood with his Trimble GeoXH 2005 GPS receiver.
MARY JOWAGNER is a Freelance Writer, Editor, and Media Consultant based in Vancouver, BC. She can be reached at mj_wagner@shaw.ca.
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